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It's hard to cut through the AI hype when there are billions of dollars at stake. I usually trust negative comments more, as long as the person isn't trying to
by demirbey05 9mo ago
It's hard to cut through the AI hype when there are billions of dollars at stake. I usually trust negative comments more, as long as the person isn't trying to sell a course. Even though Terence Tao is a respected scientist, I wonder if his recent comments are driven by a need for funding due to federal cuts. I’ve had similar experiences with LLMs—whenever I ask them about hard math or RL theory, they almost always give me the wrong answers.
- ben_w 9mo agoI also care more about the failure modes than the successes, although in my case, it's because I keep finding them exceptionally useful at software development, and I: 1. Don't want to use them where they suck. Think normalisation of deviance: "the problems haven't affected me therefore they don't exist" is a way to get really badly burned. 2. Want to train up in things they will still suck at by the time I've leared whatever it is. I find LLMs seem kinda bad at writing sheet music, and Suno is kinda bad at werid instructions (like Stable Diffusion for images), but I expect them to get good before I can. I also find them inconsistent at non-Euclidian problems: sometimes they can, sometimes they can't. I have absolutely no idea how to monetise that, but even if I could, "inconsistent" is itself an improvement on "cannot ever" which is what SOTA was a few years ago.